Question

在“移置” df之后，我有一个看起来像这样的df：

                     1     2                     3            4           5  \
level_1     questionId  type                 value  exportLabel  questionId   
0        participantId    id  -Ll4truw3KbSjVRtXmJy       Viewed    viewTime   

            6                         7            8  
level_1  type                     value  exportLabel  
0        time  2019-07-31T02:41:34.063Z      Started

如果名称匹配，如何合并值level_1的索引行并将其分成列？

新的df应该如下所示：

    questionId       type          value            exportLabel
  0  participantId    id    -Ll4truw3KbSjVRtXmJy         Viewed    
  1  viewTime         time  2019-07-31T02:41:34.063Z    Started

我尝试了groupby，但是数据通过以下代码转换回系列，索引变成了列：

df = df.groupby(df.loc['level_1'])

Answer 1

df (your data).. Generated using below

temp = StringIO("""  
                     1     2                     3            4           5   6          7            8  
level_1     questionId  type                 value  exportLabel  questionId  type      value  exportLabel   
0        participantId    id  -Ll4truw3KbSjVRtXmJy       Viewed    viewTime   time  2019-07-31T02:41:34.063Z      Started  

""")

df = pd.read_csv(temp, sep='\s+')
##df


                     1     2                     3            4           5  \
level_1     questionId  type                 value  exportLabel  questionId   
0        participantId    id  -Ll4truw3KbSjVRtXmJy       Viewed    viewTime   

            6                         7            8  
level_1  type                     value  exportLabel  
0        time  2019-07-31T02:41:34.063Z      Started

df = df.T.groupby('level_1')['0'].apply(lambda x: pd.Series(list(x))).unstack().T
del df.columns.name
print(df[['questionId','type','value','exportLabel']])

      questionId  type                     value exportLabel
0  participantId    id      -Ll4truw3KbSjVRtXmJy      Viewed
1       viewTime  time  2019-07-31T02:41:34.063Z     Started

转置数据框后如何合并所有具有相同标签的列？

1 个答案: